NCT00088699 Strong evidence from family and twin studies demonstrates that major depressive disorder (MDD) is heritable, yet there has been limited progress in identifying the actual genes involved. A separate, perhaps overlapping set of genes is expected to play a role in individual variation in treatment response in MDD. By use of a large set of markers in many genes, we seek to characterize patients who differ in their response to standard antidepressant treatments. In the first years of this project, candidate genes studies implicated a few genes in treatment outcome and other genes in adverse effects. Future studies are needed to determine whether individuals who carry such genetic markers may benefit from closer monitoring or alternative treatments. We also participated in a meta-analysis of three genome-wide association studies of antidepressant outcome. Despite greater power of this combined sample to uncover association with common genetic markers, no genome-wide significant associations were found. We concluded that no common alleles of large effect on antidepressant outcome exist in these samples. In the coming year, we are planning to re-examine this question in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) sample, using newer analysis methods that can improve on older genotyping techniques used in this sample and can also infer the presence of rarer alleles that may strongly influence treatment outcome in a minority of patients. Past work led by an extramurally-funded fellow investigated why minority participants in clinical trials drop out of treatment and experience poorer treatment response than non-minorities. The research showed that race, ethnicity, genetic ancestry, and other factors affected Selective Serotonin Reuptake Inhibitor (SSRI) treatment response, but African ancestry remained a significant risk factor for poor response, even after other factors were taken into account. We are now using new, high-throughput sequencing methods to test for rarer genetic variants that may exert larger effects, at least on treatment resistance. Such variants may show larger effects, especially among patients with unusual treatment outcomes. Patients who respond to antidepressant treatment constitute a mixture of true responders, placebo responders, and spontaneous remitters. Patients who fail to respond to multiple treatments may be less heterogeneous, since placebo responders and spontaneous remitters are removed. From over 4,000 patients enrolled in the STAR*D study, we found that only 10% show treatment resistance that is not explained by non-adherence, comorbid substance use disorder, or other factors, and only 3% are highly treatment-resistant. Sequencing of the coding regions of the genome (exome) has now been completed on 75 treatment-resistant and 25 typically responsive patients. Initial analyses have uncovered some promising leads, but additional studies in larger samples are needed. This year we have been investigating the genetic basis of treatment-resistant depression in additional samples. These include patients enrolled in studies of novel antidepressants such as ketamine and scopolamine. Additional exome sequencing is being carried out at the NIH Intramural Sequencing Center with funds provided by the NIH Clinical Center Genomics Opportunity (CCGO) program. Our current analytical strategy is based on association tests that increase power by collapsing rare variants within genes or gene sets. Gene-set and pathway enrichment analyses will be used to test whether particular biochemical or molecular pathways are over-represented among the implicated genes. Any such pathways could point to novel mechanisms of treatment resistance and would be good targets for further investigation.